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The quantitative descriptions of fault responses' characters are the chiefly presupposition of circuit fault analysis and diagnosis. Aimed to solving the deficiency of traditional information entropy theory in characters extraction of the information mutation, an energy based information entropy model is proposed to measure the complexity feature of signals. Firstly, the energy distribution uncertainty...
We propose a novel problem to simplify weighted graphs by pruning least important edges from them. Simplified graphs can be used to improve visualization of a network, to extract its main structure, or as a pre-processing step for other data mining algorithms. We define a graph connectivity function based on the best paths between all pairs of nodes. Given the number of edges to be pruned, the problem...
Bayesian network is an uncertainty inference network based on probability. Its structure learning is one of the main research techniques in the field of data mining and knowledge discovering, while constructing Bayesian network structures from data is NP hard. According to the information theory and conditional independence test, a new algorithm is presented for the construction of optimal Bayesian...
Coreference resolution is one of the most significant and difficult tasks in text mining. This paper proposes an algorithm to find coreference relations in biomedical papers. We concentrate on noun phrases referring to biomedical entities and do our research on biomedical full-text articles instead of paper abstract. The algorithm not only uses features about linguistic but also introduces features...
With the growing scale of current computing systems, traditional configuration tuning methods become less effective because they usually assume a small number of parameters in the system. In order to handle the scalability issue of configuration tuning, this paper proposes a cooperative optimization framework, which mimics the behavior of team playing to discover the optimal configuration setting...
This paper focuses on residual analysis of statistical independence of multiple variables from the viewpoint of linear algebra. The results show that multidimensional residuals are represented as linear sum of determinants of 2 × 2 submatrices, which can be viewed as information granules measuring the degree of statistical dependence.
This paper focuses on residual analysis of statistical independence of multiple variables from the viewpoint of linear algebra. The results show that multidimensional residuals are represented as linear sum of determinants of 2 × 2 submatrices, which can be viewed as information granules measuring the degree of statistical dependence.
This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal...
Several data management applications rely on data clustering methods which are usually designed to handle a static object as a single point in space. In recent years, clustering static objects seems to reach a stable point. Clustering uncertain objects is more challenging than clustering static objects and currently, it is actively studied in data mining clustering researches. In this paper, we study...
Product recommendation system has been widely used in industry especially for e-Commerce companies to solve the problem of information overload. Nonetheless, information overload is also a severe issue in custom product development practice. Sometimes customers can easily get overwhelmed by the vast number of product varieties and it is hard for them to make choices. However, the established product...
Second-order hidden Markov models (HMM2) have been widely used in pattern recognition, especially in speech recognition. Their main advantages are their capabilities to model noisy temporal signals of variable length. In this article, we introduce a new HMM2 with multiple observable sequences, assuming that all the observable sequences are statistically correlated. In this treatment, the multiple...
Assessing air traffic complexity on a mid term horizon can help to timely identify those safety-critical encounter situations that would require many tactical resolution maneuvers to be resolved. This is particularly useful in advanced autonomous air traffic management systems, where aircraft are responsible for self-separation maintenance. In this paper, we propose a new method to evaluate mid term...
An important issue arising from Web databases fuzzy query is how to rank the answers from data sources, this paper investigates the problem of ranking the answers by taking advantage of the user's needs and preferences. Firstly, based on fuzzy set theory, a satisfaction degree ranking method, which ranks the answer according to the tuple's satisfaction degree to the fuzzy query, is presented. Next,...
Domain experts are important clues to search for relevant documents in digital library information system. In this paper, we present a method to improve the document search by finding domain experts. Our method aims at exploiting the domain expertise as a rich source of evidence for document search. In particular, we propose (i) a graph-based model of the domain experts, (ii) an algorithm to find...
For multi-objective optimization problems, we introduced IPAGA (Improved Parallel Adaptive Genetic Algorithm) in this paper, a new parallel genetic algorithm which is based on Pareto Front. In this Algorithm, the non-dominated-set is constructed by the method of exclusion. The evolution population adopts the adaptive-crossover and adaptive-mutation probability, which can adjust the search scope according...
Seismic hazard analysis and vulnerability evaluation are two parts of seismic risk assessment. The form of the vulnerability evaluation procedure in HAZUS99, which is widely adopted in US and world wide, is taken as reference. A hybrid approach integrated the Simplex with the Generic Algorithm is adopted to inverse the parameters of capacity curve and fragility curve from the earthquake damage matrix...
Identifying hub nodes in public transport networks is essential for transport planning, safety evaluation and location advantage research. Some assumptions are first discussed, and a new method based on Markov chain model is proposed to measure the importance of nodes in public transport network. The transition probability is then deduced and the existence and uniqueness of solutions are presented...
The distributed denial of service attacks (DDoS) is one of the major threats to network security that exhausts network bandwidth and resources. The current detection schemes are sensitive to the number of attackers and may lead to a high false positive probability especially for large-scale networks with huge number of attackers. It is notable, however, that in the current DDoS attacks, the flooding...
The inherent properties of wireless sensor networks (WSN) disqualify most classic methods targeting timeliness guarantees. Assumptions of such methods as well as a restrictive notion of timeliness borrowed from classic real-time systems clash with the indeterminism of realistic scenarios. In this paper, we introduce a generalized notion of timeliness which allows to provide meaningful performance...
One of the most important aspects of a WSN is its localization scheme. Adequate accuracy, complexity, timing, and vulnerability to environment pitfalls are all worth considering parameters. Here, we propose discrete probabilistic DV-Hop, an enhancement to DV-Hop, a well-known range-free WSN localization algorithm, aiming to improve both its localization accuracy and complexity. One should note that...
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